CN114629905B - Energy storage system SOP optimization method and device based on cloud data - Google Patents
Energy storage system SOP optimization method and device based on cloud data Download PDFInfo
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Abstract
The invention provides an energy storage system SOP optimization method and device based on cloud data, which comprises the following steps: the battery management system collects real-time data of each single battery cell in the battery pack in real time and uploads the real-time data to the cloud platform, wherein the real-time data comprise current, voltage, static pressure difference, temperature, SOC value and SOH value of each single battery cell; the battery management system calculates the SOP value of the single battery cell according to the real-time data; the cloud platform judges whether the SOP value of the single battery cell needs to be optimized and calculated based on historical data of the single battery cell uploaded by the battery management system history. According to the invention, the battery management system collects real-time data such as current, voltage, static pressure difference, temperature, SOC value and SOH value of each single battery cell in the battery pack in real time, calculates the SOP value of each single battery cell, and evaluates whether the SOP value needs to be optimized and calculated based on historical data of the single battery cells stored in the cloud, so that the SOP differential calculation of each single battery cell is realized, and the aging difference of each single battery cell of the energy storage system is accurately evaluated.
Description
Technical Field
The invention relates to the technical field of high-speed communication and cloud storage, in particular to a method and a device for optimizing an energy storage System (SOP) based on cloud data.
Background
Under the background of rapid development of energy storage services, the retention capacity of energy storage products will increase sharply, and subtle failures will be amplified in practical application; in the whole energy storage system, the battery pack is an extremely important component, and besides the high quality requirement on the battery cell product, the service life and the safety of the battery pack are directly influenced by the related logic algorithm in the battery management system BMS.
The SOP of the existing energy storage system is obtained by acquiring the temperature, the monomer voltage and the SOH in real time based on the BMS and combining an ex-factory SOP map table (ex-factory SOP value recording table) provided by a cell factory for interpolation calculation, and has the main defects that: the onboard BMS data on the onboard energy storage system main control board is limited, the aging difference caused by the individual difference of the battery cells cannot be accurately estimated, so that the calculation of the SOP has deviation, the potential overcharge and overdischarge failure working condition affects the service life of the battery cells and other potential safety hazards.
Therefore, how to optimize the SOP differentiation calculation of each single battery cell gradually becomes a problem to be solved urgently.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the method and the device for optimizing the SOP of the energy storage system based on the cloud data can optimize the SOP differential calculation of each battery cell.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows: a cloud data-based energy storage system SOP optimization method comprises the following steps:
the method includes the steps that S1, a battery management system collects real-time data of each single battery cell in a battery pack in real time and uploads the real-time data to a cloud platform, wherein the real-time data comprise current, voltage, static pressure difference, temperature, SOC value and SOH value of each single battery cell;
s2, the battery management system calculates the SOP value of the single battery cell according to the real-time data;
and S3, the cloud platform judges whether the SOP value of the single battery cell needs to be optimized and calculated based on the historical data of the single battery cell uploaded by the battery management system history.
In order to solve the technical problem, the invention adopts another technical scheme as follows:
an energy storage system SOP optimization device based on cloud data comprises a battery management system and a cloud platform;
the battery management system is used for acquiring real-time data of each single battery cell in the battery pack in real time, calculating an SOP value of each single battery cell according to the real-time data, and uploading the real-time data to a cloud platform, wherein the real-time data comprises current, voltage, static pressure difference, temperature, SOC value and SOH value of each single battery cell;
the cloud platform is used for judging whether the SOP value of the single battery cell needs to be optimized and calculated based on the historical data of the single battery cell uploaded by the battery management system.
The invention has the beneficial effects that: the invention provides an energy storage system SOP optimization method and device based on cloud data, wherein a battery management system of an energy storage system acquires real-time data such as current, voltage, static pressure difference, temperature, SOC value and SOH value of each single battery cell in a battery pack in real time, calculates the SOP value of each single battery cell, and evaluates whether the SOP value needs to be optimized and calculated based on historical data of the single battery cells stored in the cloud, so that SOP differential calculation of each single battery cell is realized, and aging difference of each single battery cell of the energy storage system is accurately evaluated.
Drawings
Fig. 1 is an overall flowchart of an energy storage system SOP optimization method based on cloud data according to an embodiment of the present invention;
fig. 2 is a schematic block diagram illustrating components of an energy storage system in an energy storage system SOP optimization method based on cloud data according to an embodiment of the present invention;
fig. 3 is a specific flowchart of an energy storage system SOP optimization method based on cloud data according to an embodiment of the present invention;
fig. 4 is a flow of SOP optimization calculation and determination in an SOP optimization method for an energy storage system based on cloud data according to an embodiment of the present invention;
fig. 5 is a flow of SOP optimization calculation and determination in another method for SOP optimization of an energy storage system based on cloud data according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of an energy storage system SOP optimization device based on cloud data according to an embodiment of the present invention.
Description of reference numerals:
1. an energy storage system SOP optimizing device based on cloud data; 2. a battery management system; 3. and (4) cloud platform.
Detailed Description
In order to explain technical contents, achieved objects, and effects of the present invention in detail, the following description is made with reference to the accompanying drawings in combination with the embodiments.
Before that, the following explanations are made for english abbreviations and terms and the like involved in the present invention:
BMS: battery Management System, battery Management System;
SOC: state Of Charge;
SOH: state Of Health, battery Health;
and (3) SOP: state Of Power, charge-discharge Power State;
MQTT: message Queuing telemeasurement Transport protocol;
TCP/IP: transmission Control Protocol/Internet Protocol, transmission Control Protocol/Internet Protocol.
Referring to fig. 1 to 4, a method for optimizing SOP of an energy storage system based on cloud data includes the steps of:
the method includes the steps that S1, a battery management system collects real-time data of each single battery cell in a battery pack in real time and uploads the real-time data to a cloud platform, wherein the real-time data comprise current, voltage, static pressure difference, temperature, SOC value and SOH value of each single battery cell;
s2, the battery management system calculates the SOP value of the single battery cell according to the real-time data;
and S3, the cloud platform judges whether the SOP value of the single battery cell needs to be optimized and calculated based on the historical data of the single battery cell uploaded by the battery management system history.
As can be seen from the above description, the beneficial effects of the present invention are: real-time data such as current, voltage, static pressure difference, temperature, SOC value and SOH value of each monomer electricity core in the battery pack are collected in real time by energy storage system's battery management system, calculate the SOP value of each monomer electricity core to whether need optimize the calculation to the SOP value based on the historical data evaluation of the monomer electricity core of high in the clouds storage, thereby realize the SOP differentiation of each monomer electricity core and calculate, reach the ageing difference of each monomer electricity core of accurate aassessment energy storage system.
Further, the step S1 is preceded by the step of:
and S0, presetting an address space on an external memory of a main control board, wherein the address space is used for storing the factory-leaving SOP map table and the remote modification flag bit of each single battery cell, and establishing a communication protocol between the battery management system and the main control board, the battery management system acquires the factory-leaving SOP map table through the communication protocol, and the external memory is an electrified erasable programmable read-only memory.
As can be seen from the above description, by dividing an address space on an external memory of the energy storage system to pre-store the outgoing SOP map table, the battery management system can directly query and calculate the SOP value according to the outgoing SOP map table, and simultaneously set a remote modification flag bit, after SOP optimization calculation, the cloud platform can modify the corresponding SOP value in the outgoing SOP map table through the remote modification flag bit, and update the outgoing SOP map table.
Further, the step S2 specifically includes:
the battery management system inquires the charge and discharge power corresponding to the monomer battery core in an outgoing SOP map table according to the current temperature and SOC value of the monomer battery core, inquires the SOP attenuation coefficient corresponding to the monomer battery core in the outgoing SOP map table according to the current SOH value of the monomer battery core, and multiplies the charge and discharge power by the SOP attenuation coefficient to obtain the SOP value.
As can be seen from the above description, the SOP value (i.e., the charge and discharge power) can be directly obtained from the SOC value/temperature table of the battery cell, but since the health state of the battery cell is attenuated during the use of the battery cell, that is, the SOP attenuation coefficient exists, it is necessary to multiply the charge and discharge power obtained by looking up the table by the SOP attenuation coefficient, so as to ensure the accuracy of the calculated SOP value.
Further, the step S3 specifically includes:
s31, the cloud platform calls the historical data of each single battery cell in a preset time period and captures standing data in the preset time period;
and S32, the cloud platform calculates the standing pressure difference change rate of each monomer battery cell in each standing time period according to the standing time period corresponding to the standing data, if the standing pressure difference change rate is larger than a calibration threshold value, the cloud platform sends an SOP remote optimization calculation instruction to the battery management system, otherwise, the SOP optimization calculation of the monomer battery cells is not needed, and the calibration threshold value is the monthly self-discharge rate of the monomer battery cells.
According to the description, the differences of the monomer battery cells are judged through the static pressure difference change rate, so that whether the SOP value of the battery cell obtained by table lookup calculation needs to be optimized and calculated is determined according to the differences, and the accuracy of the SOP optimization evaluation of the battery cell is ensured.
Further, the step S31 further includes:
the standing judgment method of the standing data comprises the following steps:
and if the single battery cell is in a power-off state within half an hour and the current is less than 1A, the time period is the standing time period.
According to the above description, the static data needs to be powered off for at least half an hour and the current is less than 1A when the battery cell is powered off, so that the rationality of the static data is ensured, and the accuracy of the SOP optimization evaluation of the battery cell is further ensured.
Further, the step S3 specifically includes:
s31, the battery management system uploads the calculated SOP value of the single battery cell to the cloud platform;
and S32, the cloud platform calculates to obtain another SOP value according to the stored historical data and compares the SOP value with the SOP value uploaded by the battery management system, if the difference value between the SOP value and the SOP value is larger than 5% of the SOP value obtained by the cloud platform, the cloud platform sends an SOP remote optimization calculation instruction to the battery management system, the battery management system modifies the corresponding SOP value on the factory SOP map table into the SOP value obtained by the cloud platform, and otherwise, the SOP optimization calculation of the single battery cell is not required.
It can be known from the above description that, because the onboard battery management system has limited memory and less stored historical data of the battery core, the SOP can only be calculated by checking the currently stored outgoing SOP map, and the SOP differential calculation of each battery core cannot be achieved, so that a more accurate SOP value can be obtained by calculating the SOP of each battery core through a large amount of historical data stored in the cloud platform, and whether the SOP value obtained by onboard calculation is optimized or not is determined according to the difference between two sets of data by comparing the SOP values calculated by the onboard battery management system and the cloud platform, thereby further ensuring the accuracy of the SOP optimization evaluation of the battery core.
Further, the step S3 is followed by the step of:
s4, if the battery management system receives the SOP remote optimization calculation instruction sent by the cloud platform, the battery management system performs secondary confirmation on the state of the single battery cell, specifically:
judging whether the current static pressure difference of the single battery cell is larger than the static pressure difference corresponding to the SOC of 8 percent in a factory SOP map table, if so, carrying out optimization calculation on the SOP value to obtain an optimized SOP value, otherwise, directly taking the SOP value obtained in the step S2 as the optimized SOP value of the single battery cell;
and if the battery management system does not receive the SOP remote optimization calculation instruction sent by the cloud platform, directly taking the SOP value calculated in the step S2 as the optimized SOP value of the single battery cell.
From the above description, whether the optimal calculation SOP value is needed or not is finally determined through the secondary confirmation of the state of the battery cell, so that the SOP optimal calculation is prevented from being triggered by mistake, and the accuracy of the SOP optimal evaluation of the battery cell is further ensured.
Further, the step S4 of determining whether the current static voltage difference of the individual electric core is greater than the static voltage difference corresponding to the 8% soc in the factory SOP map table further includes:
if the judgment result cannot be obtained according to the outgoing SOP map table, calculating two groups of standing pressure difference change rates according to two groups of standing data of the single battery cell, if the difference value of the two groups of standing pressure difference change rates exceeds the preset monthly self-discharge rate of the single battery cell, performing SOP optimization calculation to obtain an optimized SOP value, otherwise, directly using the SOP value calculated in the step S2 as the optimized SOP value of the single battery cell, wherein the preset monthly self-discharge rate of the single battery cell is 2-5%.
As can be seen from the above description, for the cell SOP calculation value that is not directly obtained according to the factory SOP map table and that is whether the current static voltage difference of the cell is greater than the static voltage difference corresponding to the 8-percent soc in the factory SOP map table, it can be determined by another way, that is, by comparing the difference between the two sets of static voltage difference change rates, whether the SOP value needs to be optimally calculated, so as to perfect the secondary confirmation.
Further, the step S4 performs SOP optimization calculation to obtain an optimized SOP value, which specifically includes:
carrying out SOP power limiting, charging and discharging recalibration or charging cut-off voltage reduction on the SOP value of the single battery cell to obtain an optimized SOP value;
the SOP power limit is to reduce the whole SOP value;
the charging and discharging recalibration means that the cloud platform recalculates to obtain a new SOP value based on the stored historical data, replaces the corresponding SOP value in the factory SOP map table, regenerates the new SOP map table and issues the new SOP map table to the battery management system;
the charging cut-off voltage is adjusted to be the full charging cut-off point of the monomer battery cell;
after the step S4, the method further includes:
and marking the single battery cell subjected to the SOP value optimization calculation.
According to the description, the SOP value is optimized and calculated through the SOP power limiting, the charge and discharge recalibration or the charge cut-off voltage reduction, and the battery cell subjected to the SOP value optimization and calculation is marked, so that the follow-up accurate tracing is ensured.
Referring to fig. 5, an apparatus for optimizing an SOP of an energy storage system based on cloud data includes a battery management system and a cloud platform;
the battery management system is used for acquiring real-time data of each single battery cell in the battery pack in real time, calculating an SOP value of each single battery cell according to the real-time data, and uploading the real-time data to a cloud platform, wherein the real-time data comprises current, voltage, static pressure difference, temperature, SOC value and SOH value of each single battery cell;
the cloud platform is used for judging whether the SOP value of the single battery cell needs to be optimized and calculated based on the historical data of the single battery cell uploaded by the battery management system.
As can be seen from the above description, the beneficial effects of the present invention are: based on the same technical concept, the energy storage system SOP optimization method based on the cloud data is matched, an energy storage system SOP optimization device based on the cloud data is provided, a battery management system of the energy storage system collects real-time data such as current, voltage, static pressure difference, temperature, SOC value and SOH value of each single battery cell in a battery pack in real time, the SOP value of each single battery cell is calculated, whether the SOP value needs to be optimized and calculated or not is evaluated based on historical data of the single battery cells stored in the cloud, so that SOP differential calculation of each single battery cell is achieved, and aging difference of each single battery cell of the energy storage system is accurately evaluated.
The cloud data-based method and device for optimizing the SOP of the energy storage system are suitable for evaluating the aging difference of each battery cell in the energy storage system and realizing the SOP differential calculation of each battery cell, and are described below with reference to specific embodiments.
Referring to fig. 1, a first embodiment of the present invention is:
an energy storage system SOP optimization method based on cloud data is shown in FIG. 1 and comprises the following steps:
s1, a battery management system collects real-time data of each single battery cell in a battery pack in real time and uploads the real-time data to a cloud platform, wherein the real-time data comprises current, voltage, static pressure difference, temperature, SOC value and SOH value of each single battery cell;
s2, the battery management system calculates the SOP value of the single battery cell according to the real-time data;
and S3, the cloud platform judges whether the SOP value of the single battery cell needs to be optimized and calculated based on the historical data of the single battery cell uploaded by the battery management system history.
In this embodiment, the battery management system of the energy storage system collects real-time data such as current, voltage, static voltage difference, temperature, SOC value, and SOH value of each cell in the battery pack in real time, calculates the SOP value of each cell, and evaluates whether the SOP value needs to be optimized based on historical data of the cell stored in the cloud, thereby realizing SOP differential calculation of each cell and accurately evaluating the aging difference of each cell of the energy storage system.
Referring to fig. 2 to 4, a second embodiment of the present invention is:
on the basis of the first embodiment, a functional block diagram of an energy storage system used in the first embodiment is shown in fig. 2, and the energy storage system comprises a battery pack composed of all single battery cells, an Energy Management System (EMS), a main control board, an alternating current-direct current inverter (PCS), a charging source and a load, in addition to a Battery Management System (BMS) and a cloud platform related to the first embodiment. The battery pack is a controlled object of this embodiment, and includes, in addition to each individual electric core, a temperature sensor, a current/voltage sensor, a relay, a wire harness, and the like that are provided on each individual electric core; the battery management system BMS CAN estimate the relevant states of the monomer battery cells, such as SOC values, SOH values and the like, according to the real-time data of the monomer battery cells, such as voltages, currents, temperatures and the like, acquired by signal acquisition equipment, such as various sensors and the like, arranged on the monomer battery cells, and control the monomer battery cells to execute charging and discharging operations, and also transmits the acquired real-time data to a cloud platform and an energy management system EMS (energy management system) in a CAN (controller area network) or RS485 communication mode, wherein the former is used for storing various historical data of the monomer battery cells at the cloud end, and the latter is used for realizing the real-time monitoring of the monomer battery cells; the main control board is a core controller arranged in the energy storage system, and can be not limited to the naming, the main control board can receive data of each device in the energy storage system, control and protect the whole energy storage system, transparently transmit the data sent by the battery management system to the cloud platform, receive an instruction sent by the cloud platform and analyze the instruction to the battery management system, and realize the SOP optimization calculation of each single battery cell; the alternating current-direct current inverter PCS realizes the charge and discharge of the whole energy storage system through the mutual inversion of alternating current and direct current; the load and the charging source can be simply understood as electric equipment which needs to be supplied with power by the energy storage system to work and a daily power grid which can charge the energy storage system; finally, the cloud platform includes a medium for storing data, a data processing and a communication protocol (including but not limited to MQTT, TCP/IP protocol, etc.) for communicating with the energy management system and the battery management system, and implements data transmission, including uploading and issuing, by which OTA (Over-the-Air Technology) remote refreshing of each device can be implemented.
Based on the above composition framework of the energy storage system, with reference to fig. 3 and 4, in this embodiment, before step S1, the method further includes the steps of:
and S0, presetting an address space on an external memory of the main control board, wherein the address space is used for storing the factory SOP map table of each monomer battery cell and the remote modification flag bit thereof, and establishing a communication protocol between the battery management system and the main control board, the battery management system acquires the factory SOP map table through the communication protocol, and the external memory is an electrified erasable programmable read-only memory.
That is, in the present embodiment, at the beginning of the development of the on-board battery management system, it is necessary to store the variables related to the SOP calculation in a specific location of the external eeprom, and to customize the communication protocol dedicated between the on-board battery management system and the main control board. For example, in this embodiment, if the CAN bus is used for communication between the main control board and the battery management system BMS, the CAN ID of the battery management system BMS is set to 0x100, and the CAN ID of the main control board is set to 0x200, then the table 1 is referred to for the handshake protocol of the multi-frame message between the BMS and the main control board:
table 1:
then the communication source code between the battery management system and the main control board is as follows:
CAN ID
0x200 22 01// configuration requiring update of battery SOP module
0x100 01// the first byte 01 represents that the BMS can carry out SOP configuration updating at present through logic judgment, and if 00 represents that the condition is not met
CAN ID// emergency message
0x200 36 FF FF FF FF FF FF/first packet configuration data of issued battery SOP, and BMS updates specific storage position of SOP module
0x100 36// first byte 01 represents that the BMS can carry out SOP configuration updating at present through logic judgment, and if 00 represents that the condition is not met
0x200 36N FF FF FF FF FF/N packet configuration data of issued battery SOP, and BMS updates specific storage position of SOP module
0x100 36N// the first byte 01 represents that the BMS logically judges that the SOP configuration update can be performed currently, and if the value is 00, the condition is not satisfied.
The method includes the steps that an address space is divided on an external memory of the energy storage system to pre-store a factory SOP map table, so that a battery management system can conveniently and directly inquire and calculate the SOP value according to the factory SOP map table, meanwhile, a remote modification flag bit is set, and after SOP optimization calculation, a cloud platform can modify the corresponding SOP value in the factory SOP map table through the remote modification flag bit to update the factory SOP map table.
In this embodiment, step S2 specifically includes:
the battery management system inquires the charge and discharge power corresponding to the monomer battery cell in the ex-factory SOP map table according to the current temperature and SOC value of the monomer battery cell, inquires the SOP attenuation coefficient corresponding to the monomer battery cell in the ex-factory SOP map table according to the current SOH value of the monomer battery cell, and multiplies the charge and discharge power by the SOP attenuation coefficient to obtain the SOP value. For example, in this embodiment, table 2 below is a SOP table of some cells provided by a cell factory based on SOC values and temperatures:
table 2:
table 3 is a table of the relationship between SOP and SOH of a certain cell provided by a cell factory:
table 3:
| SOH | 1 | 0.95 | 0.9 | 0.85 | 0.8 |
| SOP proportionality coefficient | 1 | 0.93 | 0.88 | 0.82 | 0.75 |
That is, in this embodiment, the SOP value (charge/discharge power) may be directly obtained from the SOC value/temperature table of the battery cell, but since the state of health of the battery cell may be attenuated during the use of the battery cell, that is, the SOP attenuation coefficient exists, it is necessary to multiply the charge/discharge power obtained by looking up the table by the SOP attenuation coefficient, so as to ensure the accuracy of the calculated SOP value.
In this embodiment, as shown in fig. 4, step S3 specifically includes:
s31, calling historical data of each monomer battery cell in a preset time period by the cloud platform, and capturing standing data in the preset time period, wherein the standing data judging method comprises the following steps:
and if the single battery cell is in a power-off state within half an hour and the current is less than 1A, the time period is a standing time period.
And S32, the cloud platform calculates the static pressure difference change rate of each single battery cell in each static time period according to the static time period corresponding to the static data, if the static pressure difference change rate is larger than a calibration threshold value, the cloud platform sends an SOP remote optimization calculation instruction to the battery management system, otherwise, the SOP optimization calculation of the single battery cells is not needed, and the calibration threshold value is the monthly self-discharge rate of the single battery cells.
For example, taking the time t1 and t2 as examples, let t be2-t1 is more than or equal to 0.5h, a standing time period is set between t1 and t2, if a calibration threshold value is set to be A according to the self-discharge rate per month, and in the time period of t1 to t2, | (U) of the monomer battery core t2 -U t1 ) And if the t2-t1 | is more than or equal to A, judging that the SOP value of the single battery cell needs to be optimized and calculated. In some embodiments, the self-discharge rate of the battery is 2-5% per month, and the calibration threshold may be set to 3%, for example.
The difference of each single battery cell is judged through the static pressure difference change rate, so that whether the SOP value of the battery cell obtained by table lookup calculation needs to be optimized and calculated is determined according to the difference, and the accuracy of SOP optimization evaluation of the battery cell is ensured; meanwhile, the static data need to be electrified for at least half an hour and the current is less than 1A when the battery cell is electrified, the reasonability of the static data is ensured, and the accuracy of the SOP optimization evaluation of the battery cell is further ensured.
In addition, in this embodiment, step S3 also adopts another method, as shown in fig. 5:
and S31, uploading the calculated SOP value of the single battery cell to a cloud platform by the battery management system BMS.
And S32, the cloud platform calculates to obtain another SOP value according to the stored historical data and compares the SOP value with the SOP value uploaded by the battery management system, if the difference value of the SOP value and the SOP value is larger than 5% of the SOP value calculated by the cloud platform, the cloud platform sends an SOP remote optimization calculation instruction to the battery management system, the battery management system modifies the corresponding SOP value on the factory SOP map table into the SOP value obtained by cloud computing, and otherwise, the SOP value optimization calculation of the single battery cell is not required.
In the embodiment, the onboard battery management system has limited memory and less stored historical data of the battery cells, the SOP can only be calculated by checking the value through the currently stored factory SOP map, and the SOP differential calculation of each battery cell cannot be achieved.
In this embodiment, step S3 is followed by the step of:
s4, if the battery management system receives the SOP remote optimization calculation instruction sent by the cloud platform, the battery management system performs secondary confirmation on the state of the single battery cell, specifically:
judging whether the current static pressure difference of the single battery cell is larger than the static pressure difference corresponding to the SOC of 8 percent in the factory SOP map table, if so, carrying out optimization calculation on the SOP value to obtain an optimized SOP value, and otherwise, directly taking the SOP value obtained in the step S2 as the optimized SOP value of the single battery cell;
and if the battery management system does not receive the SOP remote optimization calculation instruction sent by the cloud platform, directly taking the SOP value calculated in the step S2 as the optimized SOP value of the single battery core.
That is, in this embodiment, when receiving an SOP remote optimization calculation instruction issued by the cloud platform, the battery management system may backup data of the outgoing SOP map table, perform secondary confirmation on the individual electric core through static pressure difference, and finally determine whether the SOP value needs to be optimized, so as to prevent the SOP optimization calculation from being triggered by mistake, and further ensure accuracy of the SOP optimization evaluation on the electric core.
In this embodiment, the step S4 of determining whether the current static differential pressure of the individual cells is greater than the static differential pressure corresponding to the 8% soc in the factory SOP map table further includes:
if the judgment result cannot be obtained according to the outgoing SOP map table, calculating two groups of standing pressure difference change rates according to two groups of standing data of the single battery cell, if the difference value of the two groups of standing pressure difference change rates exceeds the preset monthly self-discharge rate of the single battery cell, performing SOP optimization calculation to obtain an optimized SOP value, otherwise, directly using the SOP value calculated in the step S2 as the optimized SOP value of the single battery cell, wherein the monthly self-discharge rate of the preset single battery cell is 2-5%.
That is, for a cell SOP calculation value that is not directly obtained according to the factory SOP map table, whether the current static voltage difference of the cell is greater than the static voltage difference corresponding to the 8-percent soc in the factory SOP map table may be determined by another way, that is, by comparing the difference between the two sets of static voltage difference change rates, whether the SOP value needs to be optimally calculated, so as to perfect the secondary confirmation.
In step S4, performing SOP optimization calculation to obtain an optimized SOP value specifically includes:
and carrying out SOP power limiting, charging and discharging recalibration or charging cut-off voltage reduction on the SOP value of the single battery cell to obtain an optimized SOP value.
The SOP power limit is to reduce the whole SOP value, for example, a calibratable variable coefficient K is set, so as to prevent the over-discharge and over-charge of the battery core; the charging and discharging are re-calibrated, the cloud platform recalculates based on the stored historical data to obtain a new SOP value, the corresponding SOP value in the factory SOP map table is replaced, the new SOP map table is regenerated and issued to the battery management system, the power limit is similar to the SOP limit power, the purpose is to prevent the overcharge and overdischarge of the battery core, and the effects of prolonging the service life of the battery core and preventing thermal runaway are achieved; the battery cell can be effectively protected by adjusting the full charge voltage cut-off point of the single battery cell to reduce the charge cut-off voltage, so that the service life of the battery cell is prolonged, and the problem of consistency of the battery cell is solved.
In addition, step S4 is followed by:
and marking the single battery cell subjected to the SOP value optimization calculation.
In other words, in this embodiment, the SOP value is optimized and calculated by means of SOP power limiting, re-calibration of charging and discharging, or reduction of the charging cut-off voltage, and the individual electric core subjected to the SOP value optimized and calculated is marked, so that it is ensured that the subsequent accurate tracing can be performed.
Referring to fig. 6, a third embodiment of the present invention is;
on the basis of the first or second embodiment, an energy storage system SOP optimization apparatus 1 based on cloud data is provided, as shown in fig. 6, and includes a battery management system 2 and a cloud platform 3.
The battery management system 2 is used for acquiring real-time data of each single battery cell in the battery pack in real time, calculating an SOP value of each single battery cell according to the real-time data, and uploading the real-time data to the cloud platform 3, wherein the real-time data comprises current, voltage, static pressure difference, temperature, an SOC value and an SOH value of each single battery cell; the cloud platform 3 is configured to determine whether optimal calculation needs to be performed on the SOP values of the individual electric cores based on historical data of the individual electric cores uploaded historically by the battery management system 2.
That is, in this embodiment, in cooperation with the cloud data-based SOP optimization method of the first embodiment or the second embodiment, an SOP optimization device of an energy storage system based on cloud data is provided, a battery management system of the energy storage system collects real-time data such as current, voltage, static voltage difference, temperature, SOC value, and SOH value of each cell in a battery pack in real time, calculates the SOP value of each cell, and evaluates whether the SOP value needs to be optimized and calculated based on historical data of the cell stored in the cloud, thereby realizing SOP differential calculation of each cell, and achieving accurate evaluation of aging difference of each cell of the energy storage system.
In summary, the cloud data-based SOP optimization method for the energy storage system provided by the invention has the following beneficial effects:
1. the safety wave protection of the battery cell is enhanced, the situation of overcharge and overdischarge caused by the individual difference of the battery cell is prevented through SOP optimization calculation, the service life of the whole battery pack is prolonged, and the purpose of safety protection of an energy storage system is realized;
2. the system has a dual protection mechanism, SOP calculation logic of an onboard battery management system finishes various failure mode evaluation and response measures, SOP remote optimization calculation of a cloud platform is increased, a battery core can be further protected, and the probability of out-of-control is reduced;
3. in the screening process of remote SOP optimization evaluation of the electric core by the cloud platform, the electric core with the problem can be found in advance, so that a customer can be informed of the need of timely maintenance of the electric core with the problem in advance, and the customer is prevented from maintaining rights and complaints after the problem occurs;
4. the method has certain expansibility, and the related configuration of the battery management system can be modified through the cloud platform subsequently.
The above description is only an embodiment of the present invention, and not intended to limit the scope of the present invention, and all equivalent changes made by using the contents of the present specification and the drawings, or applied directly or indirectly to the related technical fields, are included in the scope of the present invention.
Claims (6)
1. A cloud data-based energy storage system SOP optimization method is characterized by comprising the following steps:
the method includes the steps that S1, a battery management system collects real-time data of each single battery cell in a battery pack in real time and uploads the real-time data to a cloud platform, wherein the real-time data comprise current, voltage, static pressure difference, temperature, SOC (state of charge) value and SOH (state of health) value of each single battery cell;
s2, the battery management system calculates the SOP value of the charge-discharge power state of the single battery cell according to the real-time data;
s3, the cloud platform judges whether the SOP value of the single battery cell needs to be optimized and calculated based on the historical data of the single battery cell uploaded by the battery management system in history;
the method also comprises the following steps before the step S1:
s0, presetting an address space on an external memory of a main control board, wherein the address space is used for storing a factory SOP map table and a remote modification flag bit of each monomer battery cell, and establishing a communication protocol between a battery management system and the main control board, the battery management system acquires the factory SOP map table through the communication protocol, and the external memory is a charged erasable programmable read-only memory;
the step S2 specifically comprises the following steps:
the battery management system inquires the charge-discharge power corresponding to the monomer battery cell in an outgoing SOP map table according to the current temperature and SOC value of the monomer battery cell, inquires the SOP attenuation coefficient corresponding to the monomer battery cell in the outgoing SOP map table according to the current SOH value of the monomer battery cell, and multiplies the charge-discharge power by the SOP attenuation coefficient to obtain the SOP value;
the step S3 specifically comprises the following steps:
s31, the cloud platform calls the historical data of each single battery cell in a preset time period and captures standing data in the preset time period;
s32, the cloud platform calculates the standing pressure difference change rate of each monomer electric core in each standing time period according to the standing time period corresponding to the standing data, if the standing pressure difference change rate is larger than a calibration threshold value, the cloud platform sends an SOP remote optimization calculation instruction to the battery management system, otherwise, the SOP optimization calculation of the monomer electric core is not needed, and the calibration threshold value is the monthly self-discharge rate of the monomer electric core;
or the like, or, alternatively,
the step S3 specifically comprises the following steps:
s31, the battery management system uploads the calculated SOP value of the single battery cell to the cloud platform;
and S32, the cloud platform calculates to obtain another SOP value according to the stored historical data and compares the SOP value with the SOP value uploaded by the battery management system, if the difference value between the SOP value and the SOP value is larger than 5% of the SOP value obtained by the cloud platform, the cloud platform sends an SOP remote optimization calculation instruction to the battery management system, the battery management system modifies the corresponding SOP value on the factory SOP map table into the SOP value obtained by the cloud platform, and otherwise, the SOP optimization calculation of the single battery cell is not required.
2. The cloud-based energy storage system SOP optimization method of claim 1, wherein the step S31 further comprises:
the standing judgment method of the standing data comprises the following steps:
and if the single battery cell is in a power-off state within half an hour and the current is less than 1A, the time period is the standing time period.
3. The cloud-based energy storage system SOP optimization method according to any one of claims 1 and 2, wherein the step S3 is followed by the step of:
s4, if the battery management system receives the SOP remote optimization calculation instruction sent by the cloud platform, the battery management system performs secondary confirmation on the state of the single battery cell, specifically:
judging whether the current static pressure difference of the single battery cell is larger than the static pressure difference corresponding to the SOC of 8 percent in a factory SOP map table, if so, carrying out optimization calculation on the SOP value to obtain an optimized SOP value, otherwise, directly taking the SOP value obtained in the step S2 as the optimized SOP value of the single battery cell;
and if the battery management system does not receive the SOP remote optimization calculation instruction sent by the cloud platform, directly taking the SOP value calculated in the step S2 as the optimized SOP value of the single battery cell.
4. The cloud-based energy storage system SOP optimization method of claim 3, wherein the step S4 of determining whether the current static voltage difference of the cell units is greater than a static voltage difference corresponding to 8% soc in a factory SOP map table further comprises:
if the judgment result cannot be obtained according to the outgoing SOP map table, calculating two groups of standing pressure difference change rates according to two groups of standing data of the single battery cell, if the difference value of the two groups of standing pressure difference change rates exceeds the preset monthly self-discharge rate of the single battery cell, performing SOP optimization calculation to obtain an optimized SOP value, otherwise, directly using the SOP value calculated in the step S2 as the optimized SOP value of the single battery cell, wherein the preset monthly self-discharge rate of the single battery cell is 2-5%.
5. The cloud-data-based energy storage system SOP optimization method of claim 4, wherein the SOP optimization calculation in the step S4 is performed to obtain an optimized SOP value, and specifically:
conducting SOP power limiting, charging and discharging recalibration or charging cut-off voltage reduction on the SOP value of the single battery cell to obtain an optimized SOP value;
the SOP power limit is to reduce the whole SOP value;
the charging and discharging recalibration means that the cloud platform recalculates to obtain a new SOP value based on the stored historical data, replaces the corresponding SOP value in the factory SOP map table, regenerates the new SOP map table and issues the new SOP map table to the battery management system;
the charging cut-off voltage is adjusted to be the full charging cut-off point of the monomer battery cell;
after the step S4, the method further includes:
and marking the single battery cell subjected to the SOP value optimization calculation.
6. An energy storage system SOP optimization device based on cloud data is characterized by comprising a battery management system and a cloud platform;
the battery management system is used for acquiring real-time data of each single battery cell in the battery pack in real time, calculating a charge-discharge power state SOP value of each single battery cell according to the real-time data, and uploading the real-time data to a cloud platform, wherein the real-time data comprises current, voltage, static pressure difference, temperature, SOC value of a charge state and SOH value of a battery health state of each single battery cell;
the cloud platform is used for judging whether the SOP value of the single battery cell needs to be optimized and calculated based on the historical data of the single battery cell uploaded by the battery management system;
the battery management system further comprises an address space, wherein the address space is preset on an external memory of the main control board and is used for storing a factory SOP map table and a remote modification flag bit of each monomer battery cell and establishing a communication protocol between the battery management system and the main control board, the battery management system acquires the factory SOP map table through the communication protocol, and the external memory is a charged erasable programmable read-only memory;
the battery management system calculates a charge-discharge power state SOP value of the single battery cell according to the real-time data, and specifically comprises the following steps:
the battery management system inquires the charge-discharge power corresponding to the monomer battery cell in an outgoing SOP map table according to the current temperature and SOC value of the monomer battery cell, inquires the SOP attenuation coefficient corresponding to the monomer battery cell in the outgoing SOP map table according to the current SOH value of the monomer battery cell, and multiplies the charge-discharge power by the SOP attenuation coefficient to obtain the SOP value;
the cloud platform judges whether the SOP value of the single battery cell needs to be optimized and calculated based on the historical data of the single battery cell uploaded by the battery management system history, and specifically comprises the following steps:
the cloud platform calls the historical data of each single battery cell in a preset time period and captures standing data in the preset time period; the cloud platform calculates the static pressure difference change rate of each monomer battery cell in each static time period according to the static time period corresponding to the static data, if the static pressure difference change rate is larger than a calibration threshold value, the cloud platform sends an SOP remote optimization calculation instruction to the battery management system, otherwise, the SOP optimization calculation of the monomer battery cells is not needed, and the calibration threshold value is the monthly self-discharge rate of the monomer battery cells;
or the like, or, alternatively,
the cloud platform calculates to obtain another SOP value according to the historical data based on the stored historical data, compares the SOP value with the SOP value uploaded by the battery management system, and sends an SOP remote optimization calculation instruction to the battery management system if the difference value between the SOP value and the SOP value is larger than 5% of the SOP value obtained by the cloud platform, and the battery management system modifies the corresponding SOP value on the factory SOP map table into the SOP value obtained by the cloud platform, otherwise, the SOP optimization calculation is not required to be carried out on the single battery cell.
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| CN116470623B (en) * | 2023-06-01 | 2023-08-29 | 苏州精控能源科技有限公司 | Large energy storage system charge and discharge power state prediction method, electronic equipment and medium |
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